Document Type : Original Article


Soil fertility describes the ability of soil to create the conditions for sustainable growth, optimum plant. The elements in the soil productive effects on soil structure, soil texture, water retention in the soil, water infiltration in the soil. On the other hand, with respect to the elements in the soil, the manure is used for different plants. One of the major goals of modern agriculture, efficient use of fertilizers. The use of chemical fertilizers, regardless of the elements in the soil, causing the balance of nutrients, loss of energy and environmental problems. So to determine the fertility of the soil due to fertilizer and plant species to determine the next Managing agricultural land is important. The parameters such as potassium, phosphorus, organic matter, copper, manganese, zinc and iron were studied. For this purpose, the data of 38 soil samples were used. Average Inverse Distance method (IDW) for mapping each element was used in GIS. In order to homogenize the data to produce a map of soil fertility phase method was used. Fuzzy membership functions were prepared using standard soil fertility. Finally, in order to ensure a different level of soil fertility maps sorted by weighted average (OWA) was used. The final results of soil fertility study area using OWA showed that risk appetite (no trade-off) is most problematic area in terms of soil fertility. So that the results showed that the class 4 and 5 areas with fertile soil and good average in the study area show a greater area than the rest of their class. However, with increasing levels of reliability and reduce the risk areas was more difficult in terms of soil fertility. So that more area in the classroom is one that has a poor soil fertility.


Statistical Data Determining the Characteristics of Soil Fertility. Agriculture Organization of Fars Province, 2013, 372p. (In Persian)
Ahmed B. 2014. Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan area, Bangladesh. Landslides, 12: 1077-1095.
Ama Azghadi A., Khorasani R., Mokarram M. and Moezi A. 2010. Soil fertility evaluation based on factors phosphorus, potassium and organic matter for plants using fuzzy AHP and GIS techniques. Water and Soil-Agricultural Sciences and Technology, 24 (5): 265-274. (In Persian)
Bill N., Schuurman N. and Hayes M.V. 2007. Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices. International Journal of Health Geographics, 6(1): 19-27.
Carlsson C., Fuller R. and Fuller S. 1997. OWA operators for doctoral student selection problem. The Ordered Weighted Averaging Operators, Springer, US, pp. 167-177.
Dobermann A., Cassman K.G., Mamaril C.P. and Sheehy S.E. 1998. Management of phosphorus, potassium, and sulfur in intensive, irrigated lowland rice. Field Crops Research, 56: 113-358.
Drobne S. and Lisec A. 2009. Multi-attribute decision analysis in GIS: weighted linear combination and ordered weighted averaging. Informatica, 33: 459-474.
Liu X. 2013. GIS-Based Local Ordered Weighted Averaging: A Case Study in London, Ontario. Electronic Thesis and Dissertation Repository. Doctoral Dissertation, The University of Western Ontario.
Malakouti M. and Gheibi M. 2000. Determine the Critical Elements of Strategic Products. Agricultural Training, Karaj, 64p. (In Persian)
Malczewski J. 2006. Integrating multicriteria analysis and geographic information systems: the ordered weighted averaging (OWA) approach. International Journal of Environmental Technology and Management, 6(1/2): 7-19.
Merigo J.M., Guillen M. and Sarabia J.M. 2015. The Ordered weighted average in the variance and the covariance. International Journal of Intelligent Systems, 30(9): 985-1005.
Mokarram M. and Aminzadeh F. 2010. Gis-based multicriteria land suitability evaluation using ordered weight averaging with fuzzy quantifier: A case study in Shavur plain, Iran. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(2): 508-512. (In Persian)
Oberthür T., Dobermann A. and Aylward M. 2000. Using auxiliary information to adjust fuzzy membership functions for improved mapping of soil quality. International Journal of Geographical Information Science, 14(5): 431-454.
Yager R.R. 1993. Families of OWA operators. Fuzzy Sets Systems, 59: 125-148.
Zhang B., Zhang Y., Chen D., Whit R.E., and Li Y. 2004. A quantitative evaluation system of soil productivity for intensive agriculture in China. Geoderma, 123: 319-33.